hello: multilvl

In enaY15/MultilevelFunctions: Multilevel Data Manipulation Functions

Description

Various functions to help with the manipulation of multilevel data. Geared towards repeated measures..

Usage

data <- countAfterEvent(df, df$event, df$nestingUnit)
data <- countBack(df, df$upwardsLimbFromCountAfterEvent, df$nestingUnit)
data <- countAfterEventContinuous(d, d$conflict, d$StudyDay, d$ElapsedTime)
data <- countBackContinuous(d, d$continuousTime, d$ElapsedTime, d$StudyDay)
data <- closestToZero(df, df$variableToZero, df$nestingUnit)

Examples

############ For discrete time (count) variable
df <- subset(d, select = c(DispName, StudyDay, row, Time, ElapsedTime, Group, conflict, reject, disagree, letd, complmnt))
df <- countAfterEvent(df, df$conflict, df$StudyDay) # Create discrete time var counting up from occurrence within day (descending limb)
df$row <- as.numeric(df$row) # Make sure row is numeric so that backwards sort in next function will work properly
df <- countBack(df, df$count, df$StudyDay) # Create discrete time var counting back from occurrence within day (ascending limb)
names(df)[colnames(df) == 'countBack'] <- 'timeConflict' # Rename generic count variable produced from function
df <- subset(df, select = -c(count)) # Remove extraneous count variable to prepare for below -- other variables' use in function

############ For continuous time variable
d <- countAfterEventContinuous(d, d$conflict, d$StudyDay, d$ElapsedTime)
d <- countBackContinuous(d, d$continuousTime, d$StudyDay)
d$limbsContinuous.conflict <- d$continuousTimeBack
d$postContinuous.conflict <- d$continuousTime
d <- subset(d, select = -c(continuousTime, continuousTimeBack))

d1.2 <- closestToZero(d1, d1$typicalTime, d1$StudyDay)
d1.2 <- subset(d1.2, select = c(DispName, StudyDay, Time, typicalTime, zeroHourConflict, time))

enaY15/MultilevelFunctions documentation built on Aug. 22, 2020, 4:42 p.m.